Civil Structural & Environ Eng (Scholarly Publications)http://hdl.handle.net/2262/204
Civil Structural & Environ Eng (Scholarly Publications)Sun, 02 Aug 2015 18:24:58 GMT2015-08-02T18:24:58ZReal time air quality forecasting using integrated parametric and non-parametric regression techniqueshttp://hdl.handle.net/2262/74147
Real time air quality forecasting using integrated parametric and non-parametric regression techniques
MISSTEAR, BRUCE; BRODERICK, BRIAN
This paper presents a model for producing real time air quality forecasts with both high accuracy and high computational efficiency. Temporal variations in nitrogen dioxide (NO2) levels and historical correlations between meteorology and NO2 levels are used to estimate air quality 48 h in advance. Non-parametric kernel regression is used to produce linearized factors describing variations in concentrations with wind speed and direction and, furthermore, to produce seasonal and diurnal factors. The basis for the model is a multiple linear regression which uses these factors together with meteorological parameters and persistence as predictors. The model was calibrated at three urban sites and one rural site and the final fitted model achieved R values of between 0.62 and 0.79 for hourly forecasts and between 0.67 and 0.84 for daily maximum forecasts. Model validation using four model evaluation parameters, an index of agreement (IA), the correlation coefficient (R), the fraction of values within a factor of 2 (FAC2) and the fractional bias (FB), yielded good results. The IA for 24 hr forecasts of hourly NO2 was between 0.77 and 0.90 at urban sites and 0.74 at the rural site, while for daily maximum forecasts it was between 0.89 and 0.94 for urban sites and 0.78 for the rural site. R values of up to 0.79 and 0.81 and FAC2 values of 0.84 and 0.96 were observed for hourly and daily maximum predictions, respectively. The model requires only simple input data and very low computational resources. It found to be an accurate and efficient means of producing real time air quality forecasts.
PUBLISHED
Thu, 01 Jan 2015 00:00:00 GMThttp://hdl.handle.net/2262/741472015-01-01T00:00:00ZSome current geotechnical research at Trinity College Dublinhttp://hdl.handle.net/2262/74032
Some current geotechnical research at Trinity College Dublin
O'KELLY, BRENDAN
PUBLISHED; Department of Civil, Structural and Environmental Engineering, Trinity College Dublin, Dublin, Ireland
Wed, 01 Jan 2014 00:00:00 GMThttp://hdl.handle.net/2262/740322014-01-01T00:00:00ZUse of miniature soil stress measuring cells under repeating loadshttp://hdl.handle.net/2262/74031
Use of miniature soil stress measuring cells under repeating loads
O'KELLY, BRENDAN
Toll D.G., Zhu H., Osman A., Coombs W., Li X. and Rouainia M.
PUBLISHED; Advances in Soil Mechanics and Geotechnical Engineering book series: Volume 3; Durham, UK.
Wed, 01 Jan 2014 00:00:00 GMThttp://hdl.handle.net/2262/740312014-01-01T00:00:00ZSome current geotechnical research at Trinity College Dublin, with a focus on instrumentation and monitoringhttp://hdl.handle.net/2262/74030
Some current geotechnical research at Trinity College Dublin, with a focus on instrumentation and monitoring
O'KELLY, BRENDAN
PUBLISHED; European Cooperation in Science and Technology (COST) Action TU1202 - Addressing the impacts of climate change on engineered slopes for infrastructure; Department of Civil and Environmental Engineering, Imperial College, London
Wed, 01 Jan 2014 00:00:00 GMThttp://hdl.handle.net/2262/740302014-01-01T00:00:00Z